• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.10
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• pp.27-34
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• 2006

This paper proposes a new method of on-line estimation for rotor resistance of the induction motor in the indirect vector controlled drive, using artificial neural network (ANN). The back propagation algorithm is used for training of the neural networks. The error between the desired state variable of an induction motor and actual state variable of a neural network model is back propagated to adjust the weight of a neural network model, so that the actual state variable tracks the desired value. The performance of rotor resistance estimator and torque and flux responses of drive, together with these estimators, are investigated variations rotor resistance from their nominal values. The rotor resistance are estimated analytically, using the proposed ANN in a vector controlled induction motor drive.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.6
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• pp.1092-1099
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• 2006

Displayed system equationally using accurate dynamic modeling of whole system including induction motor and load to analyze induction motor to normal condiction's action characteristic as well as transient characteristic using power converter device such as inverter in this paper. Also, presume adhesive power calculation through speed sensorless vector control and load torque disturbance observer for maximum tractive force control. Confirmed proposed algorithm through simulation and an experiment using railroad experiment equipment to embody control algorithm of such system. With relation of adhesive power about the wage speed by speed addition and subtraction of railway vehicle, embodied all sorts item by experiment equipment.

• Journal of Power Electronics
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• v.15 no.4
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• pp.974-986
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• 2015

A novel inverter fault-tolerant control scheme is proposed to drive brushless DC motor. A fault-tolerant inverter and its three fault-tolerant schemes (i.e., phase A fault-tolerant, phase B fault-tolerant, and phase C fault-tolerant) are analyzed. Eight voltage vectors are summarized and a voltage vector selection table is used in the control scheme to improve the midpoint current of the split capacitors. A stator flux observer is proposed. The observer can improve flux estimation, which does not require any speed adaptation mechanism and is immune to speed estimation error. Global stability of the flux observer is guaranteed by the Lyapunov stability analysis. A novel stator resistance estimator is incorporated into the sensorless drive to compensate for the effects of stator resistance variation. DC offset effects are mitigated by introducing an integral component in the observer gains. Finally, a control system based on the control scheme is established. Simulation and experiment results show that the method is correct and feasible.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.581-588
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• 2020

This study examined a brake pad wear compensation method for an Electro-Mechanical Brake (EMB) using the braking test device. A three-phase Interior Permanent Magnet Synchronous Motor (IPMSM) was applied to drive the actuator of an EMB. Current control, speed control, and position control were used to control the clamping force of the EMB. The wear compensation method was performed using a software algorithm that updates the motor model equation by comparing the motor output torque current with a reference current. In addition, a simple first-order motor model equation was applied to estimate the output clamping force. The operation time to the maximum clamping force increased within 0.1 seconds compared to the brake pad in its initial condition. The experiment verified that the reference operating time was within 0.5 seconds, and the maximum value of the clamping force was satisfied under the wear condition. The wear compensation method based on the software algorithm in this paper can be performed in the pre-departure test of rolling stock.